Data Preparation

Model your data as a series of process observations or measures that are associated with an outcome of interest.  Compose each observation as a common set of features (aka., independent variables or factors) along with the associated outcome.  Both features and outcomes are either numerical (dates, times, ages, etc.), binary (yes/no, true/false, etc.) or categorical (Gender, Service line , Floor unit, Shift, DRG, etc.).

 

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Submission

Transfer data via a secure dedicated sFTP account

  1. Our automation process will email you when data is received by our sFTP server in a HIPAA compliant HITRUST environment.
  2. Your data is automatically routed into a preprocessing stage which notifies you of errors which would stop further processing.
  3. Near real-time processing is an option

Pattern Discovery and Prediction

  1. We engineer features, as needed, to remove noise and improve the quality of findings and predictive models.
  2. We associate patterns in the data with outcomes of interest (data mining)
  3. We use multiple supervised learning algorithms, including deep learning, to both measure and verify the predictivity in the data.

 Automated Decision Rule Generation Provides Quick Insight

  1. Automatic generation of simple predictive decisioning rules allows you to easily distinguish factors associated with outcomes of interest, extract actionable factors and design corrective process interventions
  2. We can run periodic data through algorthimic learning to provide ongoing predictions based on fresh predictive models

 

News

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